CUSTOMER CHURN PREDICTION IN TELECOM INDUSTRY USING DWHBI APPROACHES AND R PROGRAMMING

Abstract

In recent days, telecom industry plays a vital role in our daily life. During corona pandemic time entire worlddependson thetelecom services domain. But telecome industry has been facing many surivival problems in the globalmarketsince last 10 years due to heavy competition between competitors. To stand in this field, service providers have to understand the complete customer requirements and provide the efficient services to stop the customer movement from one network to another network. Customer churn is one of the most critical problem faced by the telecom industry. In this industry, it is more expensive to bring the new customers as compared to retain the existing customers. The objective of customer churn prediction is to find the subscribers that are ready to move from the currentservice provider in advance. Churn prediction allows the service providers to offer new benefits and campaign offers to retain the existing customer in the same network. Technically this term would be call it as ‘Win back Situation’ in telecom industry. The high volume of data generated by telecom industry , with the help of datawarehosuing and business intelligence implementationwould become the main asset for predicting the customer churn. To prevent the churn many models and methods are used by researchers.

This research paper is using data ware housing business intelligence method, Oracle SQL developer and R programming to predict the churn result.

DWHBI model used to get the historical and current data information based on the mapping transformation logics.

Oracle SQL tool has represented to get the consistent data set from various internal & external source files by using optimizational SQL queries.

The R Tool help us to process the large level dataset churn in form of graphics, chart and different unique visualizations. R is the most powerful statistical programming tool which can represent the dataset in any kind of digital format. It also have different packages to predict the result.